A Mixed Integer Quadratic Programming Model for the Low Autocorrelation Binary Sequence Problem

Kratica, Jozef. "A Mixed Integer Quadratic Programming Model for the Low Autocorrelation Binary Sequence Problem." Serdica Journal of Computing 6.4 (2012): 385-400. <http://eudml.org/doc/250923>.

@article{Kratica2012,
abstract = {In this paper the low autocorrelation binary sequence problem (LABSP) is modeled as a mixed integer quadratic programming (MIQP) problem and proof of the model’s validity is given. Since the MIQP model is semidefinite, general optimization solvers can be used, and converge in a finite number of iterations. The experimental results show that IQP solvers, based on this MIQP formulation, are capable of optimally solving general/skew-symmetric LABSP instances of up to 30/51 elements in a moderate time. ACM Computing Classification System (1998): G.1.6, I.2.8.This research was partially supported by the Serbian Ministry of Education and Science under projects 174010 and 174033.},
author = {Kratica, Jozef},
journal = {Serdica Journal of Computing},
keywords = {Integer Programming; Quadratic Programming; Low Autocorrelation Binary Sequence Problem; integer programming; quadratic programming; low autocorrelation binary sequence problem},
language = {eng},
number = {4},
pages = {385-400},
publisher = {Institute of Mathematics and Informatics Bulgarian Academy of Sciences},
title = {A Mixed Integer Quadratic Programming Model for the Low Autocorrelation Binary Sequence Problem},
url = {http://eudml.org/doc/250923},
volume = {6},
year = {2012},
}

TY - JOUR
AU - Kratica, Jozef
TI - A Mixed Integer Quadratic Programming Model for the Low Autocorrelation Binary Sequence Problem
JO - Serdica Journal of Computing
PY - 2012
PB - Institute of Mathematics and Informatics Bulgarian Academy of Sciences
VL - 6
IS - 4
SP - 385
EP - 400
AB - In this paper the low autocorrelation binary sequence problem (LABSP) is modeled as a mixed integer quadratic programming (MIQP) problem and proof of the model’s validity is given. Since the MIQP model is semidefinite, general optimization solvers can be used, and converge in a finite number of iterations. The experimental results show that IQP solvers, based on this MIQP formulation, are capable of optimally solving general/skew-symmetric LABSP instances of up to 30/51 elements in a moderate time. ACM Computing Classification System (1998): G.1.6, I.2.8.This research was partially supported by the Serbian Ministry of Education and Science under projects 174010 and 174033.
LA - eng
KW - Integer Programming; Quadratic Programming; Low Autocorrelation Binary Sequence Problem; integer programming; quadratic programming; low autocorrelation binary sequence problem
UR - http://eudml.org/doc/250923
ER -